Internal developer portals have become essential tools for engineering organizations. As teams scale and write more lines of code than they ever imagined, the tools that help developers discover services, automate workflows, and maintain standards have moved from nice-to-have to mission-critical.
Port is one platform in this growing category. It positions itself as a developer portal focused on self-service automation and workflow orchestration. But like any tool, Port has specific strengths and limitations that make it a better fit for some organizations than others.
This guide provides an in-depth look at Port's features, use cases, and positioning in the market. More importantly, it helps you understand whether Port aligns with your organization's needs or if alternatives like Cortex, Backstage, or OpsLevel might be better choices for your specific priorities.
What is Port?
Port is an internal developer portal designed primarily for platform engineering teams, DevOps engineers, and SREs who want to streamline service management and automate infrastructure provisioning. The platform emphasizes flexibility and customization, allowing teams to define their own data models and build custom workflows for their specific needs.
Founded in Tel Aviv, Port has raised funding to build what it describes as a highly customizable developer portal. The company's core philosophy centers on giving platform teams complete control over how they structure their portal, what data they track, and how workflows are automated.
Port's customer base includes platform engineering teams at growing tech companies and organizations with strong DevOps practices. The platform appeals particularly to teams that have the resources to invest in customization and want to build workflows tailored to their specific infrastructure and processes.
However, the platform's architecture requires significant upfront configuration. Unlike some alternatives that provide out-of-the-box data models and integrations, Port operates on the principle that teams should define everything from scratch. This approach offers flexibility but comes with trade-offs in time to value and ongoing maintenance requirements.
Key use cases for Port
Port positions itself around several core use cases that align with platform engineering priorities. Understanding these use cases, and their limitations, helps clarify where Port excels and where teams might need to supplement with other tools.
Service ownership and cataloging
Port provides a service catalog that teams can customize to track services, dependencies, and ownership information. The platform allows you to define custom data models, so you can structure your catalog around your specific architecture and organizational needs.
The customization flexibility is Port's primary selling point in this area. You can define custom entities beyond just services, like teams, environments, or cloud resources, and create relationships between them. This works well for organizations with non-standard architectures that don't fit typical service catalog patterns.
However, this flexibility comes at a cost. Building and maintaining a comprehensive service catalog in Port requires significant ongoing effort. Unlike platforms that automatically discover and populate service data through integrations, Port requires manual definition of data structures and continuous configuration to keep information current. Ownership information must be manually defined and maintained in Port. It doesn't automatically sync with your identity provider or team management systems. For organizations without dedicated platform engineering resources, this maintenance burden can become substantial as teams change and services evolve.
Workflow automation and AI agents
One of Port's primary focuses is workflow automation. The platform now allows teams to build workflows that include LLM steps, which Port refers to as "AI agents" that can automate platform engineering tasks like delegating tickets or handling routine operations. Port also provides a framework for teams to build self-service workflows that developers can trigger to provision resources, create new services, or execute common tasks. These workflows can integrate with your existing tools through APIs and webhooks.
Port's workflow builder lets you create multi-step processes that can incorporate AI capabilities. For example, you might design a workflow that provisions a new Kubernetes namespace, sets up monitoring, configures CI/CD pipelines, and includes an LLM step to generate documentation or categorize requests. Port markets this as the ability to build custom AI agents for your organization.
However, these AI agents introduce additional complexity to an already configuration-heavy platform. Building these workflows demands substantial upfront investment and ongoing maintenance. Each workflow must be designed, configured, tested, and updated as your infrastructure evolves. Teams must also manage LLM integrations, prompt engineering, and the reliability challenges of incorporating AI into critical automation paths.
Port provides the framework for these workflows, but platform teams must build all the automation logic from scratch, including defining how and when to use LLM capabilities. Organizations with dedicated platform engineering teams and AI expertise can potentially extract value from this approach. For most teams, however, the configuration overhead becomes prohibitive, especially when compared to platforms like Cortex that provide pre-built workflow templates while still supporting full customization.
Self-service infrastructure provisioning
Port enables self-service infrastructure provisioning through its action framework. Developers can request resources like databases, queues, or cloud services—through Port's interface, with approval workflows and automated provisioning handled behind the scenes.
This use case works well for organizations with standardized infrastructure patterns and clear governance requirements. Platform teams can encode their standards into the provisioning workflows, ensuring that all resources meet organizational requirements for security, tagging, and configuration.
On the other hand, portability and standardization are major limitations of the platform. Because workflows and data models are custom-built for Port's specific architecture, migrating to other platforms or integrating with different tooling can require substantial rework. Organizations need to weigh the value of customization against the risk of vendor lock-in and ongoing maintenance burden.
Port's key features
Port's feature set revolves around customization and workflow automation. Understanding these capabilities, and how they compare to alternatives, helps clarify Port's positioning in the IDP landscape.
Service catalog
Port's service catalog is built on a flexible data model that teams define themselves. Rather than providing a predefined structure for services, dependencies, and teams, Port gives you a blank canvas to create custom entities and relationships.
This approach offers maximum flexibility. If your organization has unique requirements, like tracking AI models, data pipelines, or custom infrastructure patterns, Port's extensible catalog can accommodate them. You define the properties, relationships, and metadata that matter to your organization.
The trade-off is complexity and time to value. Getting a Port catalog up and running requires significant configuration work. You need to define your data model, set up integrations to populate data, and create the views and dashboards that make the catalog useful. For organizations with dedicated platform teams and complex requirements, this investment makes sense. For teams that want a catalog running quickly with minimal configuration, alternatives like Cortex provide pre-built data models and automatic discovery that deliver value in days rather than months.
AI-powered workflows and self-service actions
Port's workflow engine has evolved to include LLM capabilities, which allows teams to create self-service actions with AI steps. These workflows can integrate with any external system through webhooks, APIs, or Port's CLI, and now include the ability to add LLM processing at various steps in the automation.
The workflow builder provides a visual interface for designing multi-step processes, including approval gates, conditional logic, error handling, and LLM steps for tasks like categorization, text generation, or decision-making. Port positions this as the ability to build custom "AI agents" for your organization. Teams can create workflows for spinning up new services, provisioning infrastructure, updating configurations, or executing operational runbooks with AI assistance.
This capability adds another layer to an already complex platform. Organizations must now manage not only the workflow logic and integrations but also LLM prompt engineering, handling AI reliability issues, and determining when AI steps add value versus introducing unpredictability. As your infrastructure evolves, so too do your workflows—all of which need to be tweaked manually.
There’s an even longer list of challenges further downstream. When you add a new tool to your stack, you also need to build the integrations from scratch. Even worse, Port can’t keep up with the speed at which AI models change, which means teams need to constantly monitor and adjust prompts. Although Port provides the framework to make all of these pieces work together, sustaining these AI-powered workflows requires dedicated platform engineering resources with both infrastructure and AI expertise.
Integrations with DevOps and cloud tools
Port offers integrations with common DevOps and cloud platforms, including GitHub, GitLab, Kubernetes, AWS, and others. These integrations allow Port to pull data into your catalog and trigger external actions through workflows.
The integration model is webhook and API-based, which provides flexibility but requires more configuration than some alternatives. Rather than providing deep, pre-built integrations that automatically discover and sync data, Port's integrations often require you to define what data to pull and how to structure it in your catalog.
Cortex takes a different approach, offering over 40 pre-built integrations that automatically discover services, pull metadata, and keep information synchronized in real-time. This difference in philosophy reflects the broader trade-off between Port's customization-first approach and Cortex's time-to-value focus.
Automation
Port's automation capabilities extend beyond workflows to include scheduled jobs, event-driven actions, and automated updates to catalog entities. Teams can create automation that responds to events in their infrastructure, like a deployment completing or an incident being triggered and automatically updates relevant information in Port.
This event-driven architecture works well for organizations that want their portal to reflect real-time changes in their environment. The challenge is building and maintaining these automations. Each automation rule needs to be defined, tested, and monitored. As your infrastructure evolves, automation logic needs updating.
Reporting and dashboards
Port provides customizable dashboards that teams can build to visualize catalog data, track workflow usage, and monitor automation. These dashboards can include custom metrics, charts, and tables based on the data in your Port instance.
The reporting capabilities are functional but require configuration. Unlike platforms like Cortex that provide out-of-the-box dashboards for DORA metrics, velocity tracking, and compliance monitoring, Port requires teams to build their own reporting views. For organizations with specific reporting needs and the resources to build custom dashboards, this flexibility is valuable. For teams that want immediate visibility into standard engineering metrics, pre-built reporting provides faster time to value.
Why do companies need internal developer portals like Port?
The need for internal developer portals stems from a fundamental shift in how modern software is built and operated. Several converging trends have made selecting the right IDP a top priority for engineering teams:
Developer self-service and platform engineering: Platform engineering teams are tasked with creating "golden paths" that enable developers to provision infrastructure, spin up new services, and access resources without waiting for tickets or manual approvals. According to Gartner, 80% of software engineering organizations will establish platform engineering teams by 2026. IDPs provide the interface layer that makes self-service possible at scale.
Growing complexity in microservices and cloud-native architectures: Organizations that have migrated from monoliths to microservices face exponentially more complexity. Instead of managing one application, teams now manage hundreds or thousands of services across multiple clouds and environments. Without a centralized catalog and automation layer, this complexity creates what we call the "service discovery tax"—engineers waste hours trying to understand what services exist, who owns them, and how to use them.
Focus on improving developer experience: Developer experience has become a competitive advantage. Organizations that reduce cognitive load, eliminate context switching, and provide clear documentation see measurable improvements in productivity and retention. A Cortex market survey found that 67% of organizations struggling with IDP adoption pointed to "lack of internal alignment on information architecture" as the primary blocker to progress. The right IDP solves this by creating a single source of truth.
Standardization and governance at scale: As engineering organizations grow, maintaining consistent standards becomes increasingly difficult. How do you ensure every service has proper monitoring? How do you track compliance across hundreds of teams? IDPs provide the governance layer—through scorecards, automated checks, and reporting—that makes standards enforceable rather than aspirational.
These trends create the context for evaluating any IDP, including Port. Each platform addresses these challenges differently, with distinct trade-offs in flexibility, time to value, and feature depth.
Who should use Port?
Port's customization-first philosophy and AI agent capabilities make it a fit for specific types of organizations while potentially creating unnecessary complexity for others.
Teams with platform engineering and AI expertise
Port's new AI agents means the platform now requires expertise in both platform engineering and AI/LLM implementation. If you have engineers who can dedicate ongoing effort to building and maintaining AI-powered workflows, managing prompt engineering, handling LLM reliability challenges, defining data models, and creating integrations, Port's approach gives you the framework to build custom automation.
Teams willing to build and maintain AI-powered workflows
Port appeals to organizations that want to build custom AI agent workflows from scratch without using pre-built patterns. If you prefer defining every workflow step, LLM prompt, approval gate, and integration point yourself, Port provides that framework. However, this means taking on the additional complexity of managing AI reliability, prompt versioning, and determining when AI adds value versus introducing unpredictability. Platforms like Cortex also offer robust workflow capabilities with the advantage of pre-configured templates and embedded standards, delivering workflow automation faster while maintaining full customization options.
Teams that want to define everything manually
Port appeals to organizations that prefer defining their entire data model, entity types, and relationships manually without starting from pre-built templates. If you want the experience of building your catalog structure from a completely blank slate, Port provides that framework. However, Cortex also supports custom types and relationships while offering the option to start with proven data models, giving teams flexibility without requiring them to reinvent standard patterns.
Who might consider other solutions?
Port's customization-first approach creates challenges for several categories of organizations:
Mid-market to enterprise teams needing fast time to value: Organizations that want a developer portal running quickly, measured in days or weeks rather than months, will find Port's configuration requirements prohibitive. Cortex provides pre-built data models, automatic service discovery, and out-of-the-box integrations that deliver value immediately while still offering extensibility for custom needs.
Teams that need deep service maturity tracking and compliance monitoring: While Port can be configured to track compliance metrics, it lacks the sophisticated scorecard capabilities that platforms like Cortex provide out of the box. Cortex's scorecards offer pre-built rules for security, reliability, and production readiness standards, with automated checks against your tooling and clear reporting on compliance gaps.
Enterprises in regulated industries requiring advanced governance: Organizations in healthcare, finance, or other regulated industries need robust audit trails, role-based access controls, and compliance reporting. While Port offers basic permissions, Cortex provides enterprise-grade security features, SOC 2 Type 2 certification, and governance capabilities designed specifically for regulated environments.
Teams without dedicated platform engineering resources: Smaller engineering organizations or those just starting their platform journey will struggle with Port's configuration and maintenance requirements. The platform assumes you have engineers who can dedicate significant time to building and maintaining your IDP. Organizations without these resources should consider alternatives with lower configuration overhead, like Cortex's developer onboarding solutions that automate common setup tasks.
Teams prioritizing engineering intelligence and data-driven decision making: Port's reporting capabilities require custom configuration. Organizations that want immediate visibility into DORA metrics, cycle time analysis, and engineering health indicators will find more value in platforms like Cortex that provide these dashboards out of the box, connected to live data from your toolchain. Cortex's engineering intelligence makes it easy to track metrics that accrue to real business value like deployment frequency or SLO attainment.
Port alternatives: How does it compare to other IDPs?
Understanding Port's positioning requires comparing it to other solutions in the IDP space. Each platform makes different trade-offs between flexibility, time to value, and feature depth.
Cortex: Enterprise-grade engineering excellence platform
Cortex is an internal developer portal built specifically for mid-market to enterprise organizations that need both speed to value and sophisticated governance capabilities. Unlike Port's customization-first approach, Cortex balances pre-built functionality with extensibility.
Key differentiators:
Time to value vs. total cost of ownership: Port's pitch centers on flexibility and AI agents—you can customize anything you want and build custom AI-powered workflows. But this flexibility comes with a hidden cost: you have to define everything from scratch, including managing LLM integrations and prompt engineering. Organizations implementing Port typically spend months on initial configuration and require ongoing platform engineering resources with AI expertise to maintain workflows, integrations, data models, and AI agent reliability.
According to Forrester's Total Economic Impact study of Cortex, organizations see a 20% improvement in developer productivity and can reallocate 5 engineering headcount worth of effort previously spent on manual processes.
Cortex takes the opposite approach. The platform provides pre-built data models, automatic service discovery, and over 50 out-of-the-box integrations that deliver value in days rather than months. Services are automatically discovered from your GitHub, GitLab, or Bitbucket repositories. Metadata is automatically pulled from your CI/CD, monitoring, and incident management tools. Teams can start using Cortex's catalog, scorecards, and reporting immediately while still having complete extensibility through custom data, plugins and CQL for advanced use cases.
Live data and engineering intelligence: Cortex pulls real-time data from across your toolchain—GitHub, Kubernetes, Terraform, Datadog, PagerDuty, and dozens of other tools—ensuring teams always have an up-to-date view of their services. Instead of relying on manually updated documentation or stale service records, engineers access live insights into deployments, health metrics, incidents, and ownership.
Cortex goes beyond basic catalog functionality to provide sophisticated engineering intelligence. Out-of-the-box dashboards track DORA metrics, velocity indicators, and reliability measurements, enabling data-driven decisions about where to invest in improvements. While Port focuses on workflow automation, Cortex prioritizes keeping service data accurate, actionable, and tied to business outcomes. Cortex customers report measurable benefits like 2x deployment frequency and 67% MTTR reduction.
Enterprise-grade governance and compliance: Cortex is built for larger teams and complex engineering organizations. The platform provides role-based access control, comprehensive audit logs, and robust service ownership tracking that scales to thousands of services across multiple teams. These capabilities help enterprises manage complexity while ensuring the right people have the right level of access.
Cortex's scorecard capabilities enable organizations to define and enforce standards for production readiness, security compliance, and operational excellence. Unlike Port's custom-built approach, Cortex provides pre-configured scorecards for common standards with automated checks against your tooling. Leadership can view heatmaps of compliance across the organization, identify systemic gaps, and track progress toward goals—all without building custom reporting.
Dashboards that serve every stakeholder: Cortex provides customizable dashboards that work for both engineers and leadership. Developers get detailed, service-level insights through the Engineering Homepage including reliability metrics, ownership, and performance data. Executives and platform teams view high-level reports on service adoption, compliance, and overall platform health.
While Port's dashboards require custom configuration for each view, Cortex offers pre-built templates that teams can use immediately while still supporting full customization. This approach ensures everyone—from individual contributors to executives—can access the information they need in the format that makes sense for their role.
One-click service creation with embedded standards: Cortex enables fast, standardized service creation through developer self-service, which uses pre-configured templates to ensure new services follow engineering best practices from day one. Unlike Port, which focuses on automating processes after a service is created, Cortex helps teams establish consistency at the start. This reduces misconfigurations, deployment delays, and technical debt for fast-scaling teams that need to maintain quality while increasing velocity.
For a detailed feature comparison, explore Cortex vs. Port.
Backstage: Open-source flexibility with maintenance overhead
Backstage is Spotify's open-source developer portal that gained traction as the first widely adopted IDP solution. The platform offers complete flexibility through its plugin architecture and has a growing community of contributors.
Who uses Backstage?
Organizations with strong engineering cultures, dedicated platform teams, and the resources to maintain custom infrastructure often choose Backstage. The platform appeals to teams that want complete control over their developer portal and have the engineering capacity to build and maintain it.
Primary features:
Software catalog with customizable data models
Plugin architecture for extending functionality
Software templates for creating new services
Documentation management through TechDocs
Open-source with no licensing costs
How Backstage compares to Port and Cortex
Backstage represents the "build it yourself" end of the IDP spectrum. Like Port, it requires significant configuration and ongoing maintenance. Unlike Port, which provides a hosted platform with support, Backstage requires teams to deploy, manage, and maintain the infrastructure themselves.
The maintenance burden is substantial. Organizations running Backstage typically dedicate multiple engineers to maintaining the platform, building plugins, and keeping integrations functional as their toolchain evolves. While there's no licensing cost, the total cost of ownership—including engineering time—often exceeds commercial alternatives.
The maintenance burden is substantial. Organizations running Backstage typically dedicate multiple engineers to maintaining the platform, building plugins, and keeping integrations functional as their toolchain evolves. While there's no licensing cost, the total cost of ownership—including engineering time—often exceeds commercial alternatives. Many teams eventually realize they need to break up with Backstage and move to a more sustainable solution.
For organizations evaluating Backstage, explore Backstage vs. Cortex.
OpsLevel: Service maturity with limited scope
OpsLevel is an internal developer portal focused primarily on service maturity tracking and microservices management. The platform provides service catalogs, checks for compliance standards, and reporting on service health.
Who uses OpsLevel?
Organizations that prioritize service maturity tracking and have well-defined microservices architectures often evaluate OpsLevel. The platform works well for teams that want to enforce standards across their service fleet.
Primary features:
Service catalog with ownership tracking
Maturity checks and compliance monitoring
Integration with common DevOps tools
API-first architecture for extensibility
Reporting on service health and standards compliance
How OpsLevel compares to Port and Cortex
OpsLevel sits between Port and Cortex in terms of configuration requirements and feature depth. It provides more pre-built functionality than Port, reducing time to value, but offers less sophisticated engineering intelligence and fewer enterprise features than Cortex.
While OpsLevel focuses primarily on the service catalog and maturity tracking use case, Cortex provides a more comprehensive platform that includes engineering intelligence, developer self-service, and sophisticated governance capabilities. Organizations that need more than basic service tracking—like DORA metrics, velocity analysis, or advanced compliance reporting—will find Cortex's broader feature set delivers more value.
For a detailed comparison, see Cortex vs. OpsLevel.
Is Port the right IDP for you?
Port serves a specific niche in the IDP market. For platform engineering teams with mature practices, dedicated resources, AI expertise, and a strong preference for building custom AI-powered workflows over using pre-built functionality, Port's approach may deliver value. The platform's recent pivot to AI agents positions it for teams that want to experiment with LLM-powered automation and have the resources to manage the additional complexity.
However, the platform's limitations become clear when evaluated against the full spectrum of IDP use cases. Port requires substantial upfront configuration, ongoing maintenance, and dedicated platform engineering resources with AI expertise. The time to value is measured in months rather than days. The total cost of ownership—when accounting for engineering time spent on configuration, maintenance, prompt engineering, and managing AI reliability—often exceeds platforms with higher licensing costs but lower operational overhead.
Port's focus on AI-powered workflow automation means it lacks the sophisticated engineering intelligence, compliance tracking, and governance capabilities that enterprise organizations require. The platform provides basic catalog functionality but misses opportunities to turn that data into actionable insights about engineering health, velocity, and reliability.
For teams prioritizing service reliability, compliance monitoring, and data-driven engineering excellence, Cortex is the stronger choice. The platform delivers immediate value through automatic service discovery and pre-built integrations while maintaining complete extensibility for custom needs. Cortex's scorecards provide sophisticated compliance tracking with automated enforcement. Engineering intelligence dashboards offer visibility into DORA metrics, cycle time, and reliability indicators that enable data-driven decision making.
Most importantly, Cortex is built for scale. The platform supports thousands of services across hundreds of teams with enterprise-grade security, governance, and access controls. Organizations can start small and grow into the platform's full capabilities without hitting limitations or requiring platform re-architecture. Cortex Academy provides comprehensive training resources to help teams maximize their investment.
The question isn't whether Port can work—with sufficient investment, most platforms can be made to work. The question is whether Port is the most efficient path to the outcomes you care about. For most mid-market to enterprise organizations, the answer points toward platforms like Cortex that balance time to value with sophisticated capabilities and enterprise-grade reliability.
Ready to explore how Cortex can accelerate your engineering excellence initiatives? Explore the platform or book a demo to see it in action.
